EnvScaler: Scaling Tool-Interactive Environments for LLM Agent via Programmatic Synthesis (2026 · 5 citations)
Training LLM agents requires many stateful sandboxes in which tools can be called. Real systems are often hard to access, LLM-simulated environments hallucinate and contradict themselves, and hand-built sandboxes do not scale. EnvScaler addresses this by having LLMs write environments as executable programs instead…
ShopSimulator: Evaluating and Exploring RL-Driven LLM Agent for Shopping Assistants (2026 · 1 citation)
LLM-based shopping assistants must clarify vague requests through dialogue, use a shopper's profile and history, and pick the right item among near-identical products.

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Updated 1 November 2026